Computer Science ›› 2018, Vol. 45 ›› Issue (12): 52-60.doi: 10.11896/j.issn.1002-137X.2018.12.007

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Survey of Tire Pattern Image Retrieval Techniques

LIU Ying, ZHANG Shuai, GE Yu-xiang, WANG Fu-ping, LI Da-xiang   

  1. (Center for Image and Information Processing,Xi’an University of Posts and Telecommunications,Xi’an 710121,China)
    (Key Laboratory of Electronic Information Application Technology for Scene Investigation,Ministry of Public Security,Xi’an 710121,China)
  • Received:2018-01-15 Online:2018-12-15 Published:2019-02-25

Abstract: Tire pattern image retrieval (TPIR) plays an important role in traffic accident management and criminal case solving.Although content-based image retrieval (CBIR) has been studied for decades,and few literatures has been done in TPIR due to the lack of tire pattern data source and its special application scenario.Based on the review of the research papers in the field of TPIR in recent years,this paper provided a comprehensive survey of the state-of-the-art techniques in this area.First,this paper described the research status of TPIR by summarizing the existing techniques in low-level texture feature extraction and high-level semantic learning for tire pattern images.Then,this paper introduced tire pattern image databases appeared in literature and the performance evaluation parameters used by researchers.In addition,this paper presented experimental results testing on low-level and high-level features of tire pattern images,with results analysis provided.Lastly,considering existing techniques and practical applications,this paper discussed the research challenges in this filed and pointed out a few potential future research directions.

Key words: High-level semantic feature, Texture feature, Tire pattern image database, Tire pattern image retrieval

CLC Number: 

  • TP391.41
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